Abstract
Administrative databases contain precious information that can support the identification of specific pathologies. Specifically, chronic kidney disease (CKD) patients could be identified using hospital discharge records (HDR); these should contain information on the CKD stage using subcategories of the ICD9-CM classification’s 585 code (subcategories can be expressed just by adding a fourth digit to this code). To verify the accuracy of HDR data regarding the coding of CKD collected in the Italian region Emilia-Romagna, we analyzed the HDR records of patients enrolled in the PIRP project, which could easily be matched with eGFR data obtained through laboratory examinations. The PIRP database was used as the gold standard because it contains data on CKD patients followed up since 2004 in thirteen regional nephrology units and includes data obtained from reliable and homogeneous laboratory measurement.
All HDR of PIRP patients enrolled between 2009 and 2017 were retrieved and matched with available laboratory data on eGFR, collected within 15 days before or after discharge. We analyzed 4.168 HDR, which were classified as: a) unreported CKD (n=1.848, 44.3%); b) unspecified CKD, when code 585.9 (CKD, not specified) or 586 was used (n=446, 10.7%); c) wrong CKD (n=833, 20.0%); d) correct CKD (n=1041, 25.0%). We noticed the proportion of unreported CKD growing from 32.9% in 2009 to 56.6% in 2017, and the correspondent proportion of correct CKDs decreasing from 25.4% to 22.3%. Across disciplines, Nephrology showed the highest concordance (69.1%) between the CKD stage specified in the HDRs and the stage reported in the matched laboratory exam, while none of the other disciplines, except for Geriatrics, reached 20% concordance. When the CKD stage was incorrectly coded, it was generally underestimated; among HDRs with unreported or unspecified CKD at least half of the discharges were matched with lab exams reporting CKD in stage 4 or 5.
We found that the quality of CKD stage coding in the HDR record database was very poor, and insufficient to identify CKD patients unknown to nephrologists. Moreover, the growing proportion of unreported CKD could have an adverse effect on patients’ timely referral to a nephrologist, since general practitioners might remain unaware of their patients’ illness. Actions aimed at improving the training of the operators in charge of HDRs compilation and, most of all, at allowing the exploitation of the informative potential of HDRs for epidemiological research are thus needed.
Keywords: chronic kidney disease, hospital discharge records, administrative databases, CKD stage, identification of CKD